ArticleFrontiers in bioengineering and biotechnology2020
μBialSim: Constraint-Based Dynamic Simulation of Complex Microbiomes.
Article in Frontiers in bioengineering and biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 52 citations in OpenAlex.
- Metabolic Modelling Facilitates the Design of Synthetic Communities by Simplifying Natural Microbial Communities.Environmental microbiology · 2026Article
- MOFA: microbial optimization without forced altruism.BMC bioinformatics · 2026Article
- Dynamical Systems-Constrained Metabolic Modeling Enables Forecasting of Host-Microbiome Dynamics.bioRxiv : the preprint server for biology · 2026Article
- Constraint-Based Metabolic Modeling Approach for Microbial Communities.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Dynamic Simulation of Growth and Cross-Feeding in Microbiomes with μbialSim.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Genome-scale models in human metabologenomics.Nature reviews. Genetics · 2025Review
- Mathematical models of the colonic microbiota: an evaluation of accuracy usingFrontiers in nutrition · 2025Article
- Deciphering and designing microbial communities by genome-scale metabolic modelling.Computational and structural biotechnology journal · 2024Review
- Article
- Co-Cultivated Enzyme Constraint Metabolic Network Model for Rational Guidance in Constructing Synthetic Consortia to Achieve Optimal Pathway Allocation Prediction.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024Article
- Predicting microbial interactions with approaches based on flux balance analysis: an evaluation.BMC bioinformatics · 2024Article
- Community-scale models of microbiomes: Articulating metabolic modelling and metagenome sequencing.Microbial biotechnology · 2024Review
- Microbiome modeling: a beginner's guide.Frontiers in microbiology · 2024Review
- A new era of synthetic biology-microbial community design.Synthetic biology (Oxford, England) · 2024Review
- A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia.PLoS computational biology · 2023Article
- Assumptions on decision making and environment can yield multiple steady states in microbial community models.BMC bioinformatics · 2023Article
- Microbiome distribution modeling using gradient descent strategies for mock, in vitro and clinical community distributions.PloS one · 2023Article
- Metabolomics and modelling approaches for systems metabolic engineering.Metabolic engineering communications · 2022Review
- COMMIT: Consideration of metabolite leakage and community composition improves microbial community reconstructions.PLoS computational biology · 2022Article
- Emerging computational paradigms to address the complex role of gut microbial metabolism in cardiovascular diseases.Frontiers in cardiovascular medicine · 2022Review
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microbial communities are pervasive in the natural environment, associated with many hosts, and of increasing importance in biotechnological applications. The complexity of these microbial systems makes the underlying mechanisms driving their dynamics difficult to identify. While experimental meta-OMICS techniques are routinely applied to record the inventory and activity of microbiomes over time, it remains difficult to obtain quantitative predictions based on such data. Mechanistic, quantitative mathematical modeling approaches hold the promise to both provide predictive power and shed light on cause-effect relationships driving these dynamic systems. We introduce μbialSim (pronounced "microbial sim"), a dynamic Flux-Balance-Analysis-based (dFBA) numerical simulator which is able to predict the time course in terms of composition and activity of microbiomes containing 100s of species in batch or chemostat mode. Activity of individual species is simulated by using separate FBA models which have access to a common pool of compounds, allowing for metabolite exchange. A novel augmented forward Euler method ensures numerical accuracy by temporarily reducing the time step size when compound concentrations decrease rapidly due to high compound affinities and/or the presence of many consuming species. We present three exemplary applications of μbialSim: a batch culture of a hydrogenotrophic archaeon, a syntrophic methanogenic biculture, and a 773-species human gut microbiome which exhibits a complex and dynamic pattern of metabolite exchange. Focusing on metabolite exchange as the main interaction type, μbialSim allows for the mechanistic simulation of microbiomes at their natural complexity. Simulated trajectories can be used to contextualize experimental meta-OMICS data and to derive hypotheses on cause-effect relationships driving community dynamics based on scenario simulations. μbialSim is implemented in Matlab and relies on the COBRA Toolbox or CellNetAnalyzer for FBA calculations. The source code is available under the GNU General Public License v3.0 at https://git.ufz.de/UMBSysBio/microbialsim.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.